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arXiv · 2312.16933

EvPlug: Learn a Plug-and-Play Module for Event and Image Fusion

Jianping Jiang·Xinyu Zhou·Peiqi Duan·Boxin Shi
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Abstract

Event cameras and RGB cameras exhibit complementary characteristics in imaging: the former possesses high dynamic range (HDR) and high temporal resolution, while the latter provides rich texture and color information. This makes the integration of event cameras into middle- and high-level RGB-based vision tasks highly promising. However, challenges arise in multi-modal fusion, data annotation, and model architecture design. In this paper, we propose EvPlug, which learns a plug-and-play event and image fusion module from the supervision of the existing RGB-based model. The learned fusion module integrates event streams with image features in the form of a plug-in, endowing the RGB-based model to be robust to HDR and fast motion scenes while enabling high temporal resolution inference. Our method only requires unlabeled event-image pairs (no pixel-wise alignment required) and does not alter the structure or weights of the RGB-based model. We demonstrate the superiority of EvPlug in several vision tasks such as object detection, semantic segmentation, and 3D hand pose estimation

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Jianping Jiang, Xinyu Zhou, Peiqi Duan, Boxin Shi. 2023-12-28. EvPlug: Learn a Plug-and-Play Module for Event and Image Fusion. https://arxiv.org/abs/2312.16933

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